In this paper, an (s, S) policy is determined by using a simulation-optimization approach for a periodic review inventory system at a pharmacy department of a major hospital in Thailand. The simulation, which imitates the inventory system behavior, is constructed on a spreadsheet, while the cyclic coordinate method with a golden section search is adopted as the optimization algorithm. Solutions for the policy's parameters from the search algorithm are evaluated using the simulation, which features randomly generated demand and lead time data from empirical distributions of actual datasets. The objective is to minimize the total inventory cost, including ordering, holding, and shortage costs. This model is applied for 10 medicine items, selected as representatives of the entire item range in the pharmacy department. According to the simulation results, a minimal cost inventory policy for each item is obtained within a short amount of run time. This indicates the effectiveness and efficiency of the proposed approach for this type of problem.